There are major threats to Bangladesh's food and health security posed by climate change, including a higher risk of food shortage, hunger, and waterborne illnesses. The country's coastline regions, which are most susceptible to the effects of climate change, are where these problems are most severe. The influence of climate change on Bangladesh's food and health security is examined in this research study. The report analyzes the existing level of understanding on this subject, identifies knowledge gaps, and proposes future research possibilities. Based on the literature review study found a number of issues, such as crop failure and lower health status that worsen the effects of climate change on food and health security. The evaluation emphasizes the serious threats that climate change poses to Bangladesh's food and health security, such as a higher risk of food shortage, hunger, and waterborne illnesses. The harshest effects of climate change are on people's health. The report makes a number of suggestions for academics and politicians to address these issues and how policymakers and scholars may approach these problems.
{"title":"Food and health security impact of climate change in Bangladesh: a review","authors":"Monira Parvin Moon","doi":"10.2166/wcc.2023.131","DOIUrl":"https://doi.org/10.2166/wcc.2023.131","url":null,"abstract":"\u0000 There are major threats to Bangladesh's food and health security posed by climate change, including a higher risk of food shortage, hunger, and waterborne illnesses. The country's coastline regions, which are most susceptible to the effects of climate change, are where these problems are most severe. The influence of climate change on Bangladesh's food and health security is examined in this research study. The report analyzes the existing level of understanding on this subject, identifies knowledge gaps, and proposes future research possibilities. Based on the literature review study found a number of issues, such as crop failure and lower health status that worsen the effects of climate change on food and health security. The evaluation emphasizes the serious threats that climate change poses to Bangladesh's food and health security, such as a higher risk of food shortage, hunger, and waterborne illnesses. The harshest effects of climate change are on people's health. The report makes a number of suggestions for academics and politicians to address these issues and how policymakers and scholars may approach these problems.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44539970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study employed the Decision-Scaling (DS) approach and the IHACRES (Identification of unit Hydrographs And Component flows from Rainfall) long-term runoff model to investigate the impact of composite changes in rainfall and temperature on dam inflows at Chungju dam, Yongdam dam, Hapcheon dam, and Seomjingang dam basins. By analyzing flow regimes, rainfall scenarios, and temperature scenarios, the study revealed crucial insights into dam inflow and its response to climate stressors. The findings demonstrated that the rate of inflow increase in the study basins exceeded the rate of rainfall increase, indicating the significance of basin storage effects in contributing to runoff generation. The analysis of rainfall changes by quantile highlighted the dominant influence of the upper-high (UH) rainfall quantile, which led to higher flood inflow compared to other quantiles. Furthermore, scenarios with different rainfall patterns were compared, showcasing the predominant impact of UH quartile rainfall on the total inflow variation. The study also analyzed the runoff ratio, finding that changes in precipitation proportionally affected the runoff ratio. Overall, these insights contribute to understanding the sensitivity of dams to changes in rainfall and temperature, facilitating the development of strategies for sustainable water supply and flood management in dam systems.
采用Decision-Scaling (DS)方法和ihaacres (Identification of unit Hydrographs and Component flows from Rainfall)长期径流模型，研究了降雨和温度复合变化对忠州坝、龙潭坝、陕川坝和西津江坝流域大坝入流的影响。通过分析水流状况、降雨情景和温度情景，该研究揭示了大坝流入及其对气候压力的反应的关键见解。研究结果表明，流域入流增幅大于降水增幅，表明流域蓄水效应对产流的贡献具有重要意义。对降水变化的分位数分析表明，上高降水分位数的影响占主导地位，与其他分位数相比，上高降水分位数的影响更大。此外，比较了不同降雨模式的情景，显示了UH四分位数降雨对总入流变化的主要影响。研究还分析了径流比，发现降水的变化成比例地影响了径流比。总的来说，这些见解有助于理解水坝对降雨和温度变化的敏感性，促进水坝系统可持续供水和洪水管理战略的发展。
{"title":"Climate stress impacts on the reservoir inflows: a decision-scaling and IHACRES modeling approach in South Korean basins","authors":"Taehyeon Kim, B. Kang","doi":"10.2166/wcc.2023.156","DOIUrl":"https://doi.org/10.2166/wcc.2023.156","url":null,"abstract":"\u0000 This study employed the Decision-Scaling (DS) approach and the IHACRES (Identification of unit Hydrographs And Component flows from Rainfall) long-term runoff model to investigate the impact of composite changes in rainfall and temperature on dam inflows at Chungju dam, Yongdam dam, Hapcheon dam, and Seomjingang dam basins. By analyzing flow regimes, rainfall scenarios, and temperature scenarios, the study revealed crucial insights into dam inflow and its response to climate stressors. The findings demonstrated that the rate of inflow increase in the study basins exceeded the rate of rainfall increase, indicating the significance of basin storage effects in contributing to runoff generation. The analysis of rainfall changes by quantile highlighted the dominant influence of the upper-high (UH) rainfall quantile, which led to higher flood inflow compared to other quantiles. Furthermore, scenarios with different rainfall patterns were compared, showcasing the predominant impact of UH quartile rainfall on the total inflow variation. The study also analyzed the runoff ratio, finding that changes in precipitation proportionally affected the runoff ratio. Overall, these insights contribute to understanding the sensitivity of dams to changes in rainfall and temperature, facilitating the development of strategies for sustainable water supply and flood management in dam systems.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44963808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study focuses on the influences of climate change on drought characteristics in the small, data-scarce Ndembera River catchment in Tanzania, using the Climatic Research Unit (CRU) datasets and six regional climate models (RCMs) of the CORDEX-Africa framework. The RCM simulations were validated against the CRU data, and their optimistic (RCP 2.6) and worst-case (RCP 8.5) scenarios were used in estimating ensemble simulations using the random forest regression. The ensemble simulations were used to compute standardized precipitation evapotranspiration indices, which characterized drought for the near-future, mid-future, and far-future. Finally, patterns and trends of changes in temperature and precipitation were compared to those in drought characteristics. The findings revealed substantial uncertainty in RCMs, although their ensembles fairly reproduced the historical climate in the catchment. Under the optimistic scenario, a slight decrease in precipitation and a small increase in maximum temperature are projected. Consequently, drought intensity is projected to rise just slightly but remain moderate throughout this century. These changes are expected to be more pronounced during the near-future than the far-future. Under the worst-case scenario, the projected changes are expected to be more pronounced, especially during the end of the century. These sorts of insights are vital for enhancing adaptations to climate change in catchments.
{"title":"Investigating the influences of climate change on drought in a small data-scarce river catchment","authors":"F. Wambura","doi":"10.2166/wcc.2023.291","DOIUrl":"https://doi.org/10.2166/wcc.2023.291","url":null,"abstract":"\u0000 \u0000 This study focuses on the influences of climate change on drought characteristics in the small, data-scarce Ndembera River catchment in Tanzania, using the Climatic Research Unit (CRU) datasets and six regional climate models (RCMs) of the CORDEX-Africa framework. The RCM simulations were validated against the CRU data, and their optimistic (RCP 2.6) and worst-case (RCP 8.5) scenarios were used in estimating ensemble simulations using the random forest regression. The ensemble simulations were used to compute standardized precipitation evapotranspiration indices, which characterized drought for the near-future, mid-future, and far-future. Finally, patterns and trends of changes in temperature and precipitation were compared to those in drought characteristics. The findings revealed substantial uncertainty in RCMs, although their ensembles fairly reproduced the historical climate in the catchment. Under the optimistic scenario, a slight decrease in precipitation and a small increase in maximum temperature are projected. Consequently, drought intensity is projected to rise just slightly but remain moderate throughout this century. These changes are expected to be more pronounced during the near-future than the far-future. Under the worst-case scenario, the projected changes are expected to be more pronounced, especially during the end of the century. These sorts of insights are vital for enhancing adaptations to climate change in catchments.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46966295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kehase Neway Gebretsadkan, Melsew Berihun Tamrie, Haile Belay Desta
Satellite rainfall products are good options to overcome shorter records, record challenges, and inconsistencies with rain gauges. However, satellites' rainfall retrieval algorithms are region- and time scale-specific; hence, its key concern is the selection of appropriate satellite products. Accordingly, this study evaluates the performance of five high-resolution satellites' rainfall qualitatively, using multiple categorical metrics, and quantitatively by hybrid techniques at multiple metrics for daily and monthly scales. The result showed that Climate Prediction Center (CPC) Morphing Algorithm (CMORPH.CPC) performed better by scoring: qualitatively; Critical Success Index (CSI = 0.856), Probability of Detection (POD = 0.911), Frequency Bias Index (FBI = 0.974), and quantitatively; correlation coefficient (CC = 0.375), Root Mean Square Error (RMSE ≈ 575), and Volumetric Critical Success Index (VCSI = 0.958) at a daily scale. At a monthly scale, Climate Hazards Group Infrared Precipitation with Stations (CHIRPS.v2) performed better by scoring CSI = 0.983, POD = 1 and FBI = 0.975 qualitatively, and quantitatively, CC = 0.836 with strong VCSI = 0.981 and better RMSE (≈125) than daily. The daily rainfall of these satellites needs value-improving techniques before using them in place of Gidabo's rain gauge rainfall, while the rainfall of CHIRPS.v2 at a monthly scale can be an alternative source of rainfall data. Finally, it ensured that for the Gidabo catchment and elsewhere with similar features, the performance of satellite rainfall products was more effective at a monthly scale than at a daily scale.
{"title":"Performance evaluation of multi-satellite rainfall products in the Gidabo catchment, Rift Valley Basin, Ethiopia","authors":"Kehase Neway Gebretsadkan, Melsew Berihun Tamrie, Haile Belay Desta","doi":"10.2166/wcc.2023.097","DOIUrl":"https://doi.org/10.2166/wcc.2023.097","url":null,"abstract":"\u0000 \u0000 Satellite rainfall products are good options to overcome shorter records, record challenges, and inconsistencies with rain gauges. However, satellites' rainfall retrieval algorithms are region- and time scale-specific; hence, its key concern is the selection of appropriate satellite products. Accordingly, this study evaluates the performance of five high-resolution satellites' rainfall qualitatively, using multiple categorical metrics, and quantitatively by hybrid techniques at multiple metrics for daily and monthly scales. The result showed that Climate Prediction Center (CPC) Morphing Algorithm (CMORPH.CPC) performed better by scoring: qualitatively; Critical Success Index (CSI = 0.856), Probability of Detection (POD = 0.911), Frequency Bias Index (FBI = 0.974), and quantitatively; correlation coefficient (CC = 0.375), Root Mean Square Error (RMSE ≈ 575), and Volumetric Critical Success Index (VCSI = 0.958) at a daily scale. At a monthly scale, Climate Hazards Group Infrared Precipitation with Stations (CHIRPS.v2) performed better by scoring CSI = 0.983, POD = 1 and FBI = 0.975 qualitatively, and quantitatively, CC = 0.836 with strong VCSI = 0.981 and better RMSE (≈125) than daily. The daily rainfall of these satellites needs value-improving techniques before using them in place of Gidabo's rain gauge rainfall, while the rainfall of CHIRPS.v2 at a monthly scale can be an alternative source of rainfall data. Finally, it ensured that for the Gidabo catchment and elsewhere with similar features, the performance of satellite rainfall products was more effective at a monthly scale than at a daily scale.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41861316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The uncertainty in the climate projection arising from various climate models is very common, and averaging such results poses a risk of underestimation or sometimes overestimation of impact in magnitude and frequency. Further, the performance of various climate models in monsoon degrades drastically due to the skewed nature. Under these circumstances, the performance of the climate model in the monsoon and non-monsoon periods is critical for accurate assessment. A multimodal approach has been used in the present work to quantify the uncertainty involved in the climate model using reliability ensemble averaging (REA). Based on AR6 of IPCC, the ensemble of 26 GCMs was used to evaluate the model performance and possible change in seasonal precipitation in four cities with distinct climate conditions, namely, Coimbatore, Rajkot, Udaipur, and Siliguri. The results show that non-monsoon and monsoon rainfall are expected to increase in all the regions. Most of the models perform poorly in simulating monsoon climate, especially in the monsoon period and are highly inconsistent spatially. The study also finds that the model performance is largely linked to the ratio of natural variability and mean.
{"title":"Multimodal climate change prediction in a monsoon climate","authors":"S. Mohan, Akash Sinha","doi":"10.2166/wcc.2023.393","DOIUrl":"https://doi.org/10.2166/wcc.2023.393","url":null,"abstract":"\u0000 The uncertainty in the climate projection arising from various climate models is very common, and averaging such results poses a risk of underestimation or sometimes overestimation of impact in magnitude and frequency. Further, the performance of various climate models in monsoon degrades drastically due to the skewed nature. Under these circumstances, the performance of the climate model in the monsoon and non-monsoon periods is critical for accurate assessment. A multimodal approach has been used in the present work to quantify the uncertainty involved in the climate model using reliability ensemble averaging (REA). Based on AR6 of IPCC, the ensemble of 26 GCMs was used to evaluate the model performance and possible change in seasonal precipitation in four cities with distinct climate conditions, namely, Coimbatore, Rajkot, Udaipur, and Siliguri. The results show that non-monsoon and monsoon rainfall are expected to increase in all the regions. Most of the models perform poorly in simulating monsoon climate, especially in the monsoon period and are highly inconsistent spatially. The study also finds that the model performance is largely linked to the ratio of natural variability and mean.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47966776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Water quality has become a significant concern in many river basins in China due to both point and non-point source pollution. The SWAT model assessed pollution reduction scenarios and their effects on Donghe River basin water quality in southwest China. The calibrated model evaluated existing point and non-point emissions. Three schemes reduced point sources by 30, 60, and 90% and non-point sources by 25, 50, and 75%, respectively. Simulations analyzed annual and monthly total phosphorus (TP) concentrations under the scenarios. Results showed that the scenarios effectively improved water quality, meeting Class IV TP standards annually. However, TP exceeded standards in dry months (January–April, December) under all scenarios. A certain degree of negative correlation (R = −0.52, P = 0.11) between TP and rainfall suggests rainfall that influences TP. Comprehensive measures are needed to achieve standards year-round. In summary, the study found that reducing emissions improved Donghe water quality overall but more work is required to meet standards during dry periods. Rainfall correlates with and may affect TP. The work emphasizes implementing comprehensive approaches for year-round water quality improvements in the basin.
{"title":"Evaluating the effects of different pollution reduction scenarios on the total phosphorus concentration of a mountainous river basin in southwest China using SWAT model: a case study of the Donghe River in Baoshan, Yunnan","authors":"Yongjian Wang, Chang-jun Zhu, Chunming Hu, Wenlong Hao","doi":"10.2166/wcc.2023.104","DOIUrl":"https://doi.org/10.2166/wcc.2023.104","url":null,"abstract":"\u0000 \u0000 Water quality has become a significant concern in many river basins in China due to both point and non-point source pollution. The SWAT model assessed pollution reduction scenarios and their effects on Donghe River basin water quality in southwest China. The calibrated model evaluated existing point and non-point emissions. Three schemes reduced point sources by 30, 60, and 90% and non-point sources by 25, 50, and 75%, respectively. Simulations analyzed annual and monthly total phosphorus (TP) concentrations under the scenarios. Results showed that the scenarios effectively improved water quality, meeting Class IV TP standards annually. However, TP exceeded standards in dry months (January–April, December) under all scenarios. A certain degree of negative correlation (R = −0.52, P = 0.11) between TP and rainfall suggests rainfall that influences TP. Comprehensive measures are needed to achieve standards year-round. In summary, the study found that reducing emissions improved Donghe water quality overall but more work is required to meet standards during dry periods. Rainfall correlates with and may affect TP. The work emphasizes implementing comprehensive approaches for year-round water quality improvements in the basin.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48908973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Baro Akobo River, Gambella, is a representative of lower Baro River watersheds with lost soils. Under eight landscapes, the geospatial and temporal variability of water use efficiency (WUE) and system WUE (sWUE) was investigated. In contrast with WUE, sWUE takes runoff into account, better capturing the combined effects of soil management, climate change, and land cover change on agricultural irrigation systems. The total area of the lower Baro River is 20,325. This study used GIS, RS, EasyFit, and CROPWAT8.0 software. It allows automatic fitting distributions to the data, selects the best mathematical tool, and quantifies the yields and WUE/sWUE. sWUE is a more helpful index than WUE to describe differences in water holding capacity and yield across agricultural landscapes. sWUE varies in streamflow from its correlation with runoff, with a coefficient of variation (CV) of 71% across the watershed. Evapotranspiration (ET) had a CV of 70%. Temporally, sWUE will decrease by 10% by 2050, but its spatial variability will reach 25%. These methods improve soil infiltration and water storage, which reduce runoff and standing water lost through ET and raise sWUE.
{"title":"Integrated spatial and temporal variability of the system water use efficiency in a lower Baro River watershed, Ethiopia","authors":"Fiseha Befikadu, Amba Shetty, F. Fufa","doi":"10.2166/wcc.2023.171","DOIUrl":"https://doi.org/10.2166/wcc.2023.171","url":null,"abstract":"\u0000 The Baro Akobo River, Gambella, is a representative of lower Baro River watersheds with lost soils. Under eight landscapes, the geospatial and temporal variability of water use efficiency (WUE) and system WUE (sWUE) was investigated. In contrast with WUE, sWUE takes runoff into account, better capturing the combined effects of soil management, climate change, and land cover change on agricultural irrigation systems. The total area of the lower Baro River is 20,325. This study used GIS, RS, EasyFit, and CROPWAT8.0 software. It allows automatic fitting distributions to the data, selects the best mathematical tool, and quantifies the yields and WUE/sWUE. sWUE is a more helpful index than WUE to describe differences in water holding capacity and yield across agricultural landscapes. sWUE varies in streamflow from its correlation with runoff, with a coefficient of variation (CV) of 71% across the watershed. Evapotranspiration (ET) had a CV of 70%. Temporally, sWUE will decrease by 10% by 2050, but its spatial variability will reach 25%. These methods improve soil infiltration and water storage, which reduce runoff and standing water lost through ET and raise sWUE.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48894096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Groundwater use has significantly increased in the rapidly urbanising city of Kumasi, Ghana. But there is a lack of understanding of whether the groundwater system can sustain the growing demand in the future amidst climate change and rapid urbanisation. Using remote sensing datasets and a water balance approach, this study estimated the groundwater recharge and assessed how urbanisation has affected its groundwater sustainability. Sustainability is investigated by comparing multi-annual groundwater withdrawals to long-term average annual replenishment. Results show that while groundwater recharge has decreased by 80% from 1986 to 2020, mainly due to substantial (63%) loss of permeable land, groundwater consumption has seen a six-fold increase. Groundwater consumption in 2020 exceeded the long-term average groundwater recharge by 2.2 Mm3, suggesting that the current groundwater use trends are unsustainable for future groundwater availability. Under a ‘business-as-usual’ scenario, a four-fold increase in groundwater consumption is predicted by 2050 while climate change and land cover changes may reduce groundwater recharge by 10 and 55%, respectively. Practical measures such as promoting artificial groundwater replenishment approaches, adopting low-impact development and instituting demand management measures must be implemented in the Metropolis. This should be informed by further studies to ascertain the exact condition of the groundwater.
{"title":"Bridging the data gap: using remote sensing and open-access data for assessing sustainable groundwater use in Kumasi, Ghana","authors":"Estela Fernandes Potter, I. Monney, M. Rutten","doi":"10.2166/wcc.2023.261","DOIUrl":"https://doi.org/10.2166/wcc.2023.261","url":null,"abstract":"\u0000 \u0000 Groundwater use has significantly increased in the rapidly urbanising city of Kumasi, Ghana. But there is a lack of understanding of whether the groundwater system can sustain the growing demand in the future amidst climate change and rapid urbanisation. Using remote sensing datasets and a water balance approach, this study estimated the groundwater recharge and assessed how urbanisation has affected its groundwater sustainability. Sustainability is investigated by comparing multi-annual groundwater withdrawals to long-term average annual replenishment. Results show that while groundwater recharge has decreased by 80% from 1986 to 2020, mainly due to substantial (63%) loss of permeable land, groundwater consumption has seen a six-fold increase. Groundwater consumption in 2020 exceeded the long-term average groundwater recharge by 2.2 Mm3, suggesting that the current groundwater use trends are unsustainable for future groundwater availability. Under a ‘business-as-usual’ scenario, a four-fold increase in groundwater consumption is predicted by 2050 while climate change and land cover changes may reduce groundwater recharge by 10 and 55%, respectively. Practical measures such as promoting artificial groundwater replenishment approaches, adopting low-impact development and instituting demand management measures must be implemented in the Metropolis. This should be informed by further studies to ascertain the exact condition of the groundwater.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48369278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joel Hernández-Bedolla, A. Solera, S. T. Sánchez-Quispe, Constantino Domínguez-Sánchez
Evapotranspiration is one of the most significant variables used to determine runoff, hydrological balances, and climate change studies. In semi-arid conditions, there is a need to evaluate various alternatives to establish reference evapotranspiration (ETo), given that climate change scenarios sometimes do not provide information on diverse climate variables. Several alternatives for obtaining evapotranspiration are analyzed in this study and compared with the Penman-Monteith method, modified by FAO (PMFAO56). Due to limited daily climate information, it is necessary to consider different options for determining reference evapotranspiration. In the present work, methods based on temperature (Hargreaves, Hargreaves 1, Hargreaves 2, and Baier-Robertson) and radiation (Caprio, Irmark 1, Irmark 2, Irmark 3, Makkink, Priestley-Taylor and Hasen) were investigated. The best performance for the semi-arid Jucar River Basin was determined by Hargreaves methods. Regional calibration of Hargreaves methods, Hargreaves 1 and Hargreaves 2, were performed for each sub-basin.
{"title":"Comparative analysis of 12 reference evapotranspiration methods for semi-arid regions (Spain)","authors":"Joel Hernández-Bedolla, A. Solera, S. T. Sánchez-Quispe, Constantino Domínguez-Sánchez","doi":"10.2166/wcc.2023.448","DOIUrl":"https://doi.org/10.2166/wcc.2023.448","url":null,"abstract":"\u0000 \u0000 Evapotranspiration is one of the most significant variables used to determine runoff, hydrological balances, and climate change studies. In semi-arid conditions, there is a need to evaluate various alternatives to establish reference evapotranspiration (ETo), given that climate change scenarios sometimes do not provide information on diverse climate variables. Several alternatives for obtaining evapotranspiration are analyzed in this study and compared with the Penman-Monteith method, modified by FAO (PMFAO56). Due to limited daily climate information, it is necessary to consider different options for determining reference evapotranspiration. In the present work, methods based on temperature (Hargreaves, Hargreaves 1, Hargreaves 2, and Baier-Robertson) and radiation (Caprio, Irmark 1, Irmark 2, Irmark 3, Makkink, Priestley-Taylor and Hasen) were investigated. The best performance for the semi-arid Jucar River Basin was determined by Hargreaves methods. Regional calibration of Hargreaves methods, Hargreaves 1 and Hargreaves 2, were performed for each sub-basin.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48167326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Ghorbani, M. Salarijazi, Sedigheh Bararkhanpour, Laleh Rezaei Ghaleh
This research utilized Bayesian and quantile regression techniques to analyze trends in discharge levels across various seasons for three stations in the Gorganroud basin of northern Iran. The study spanned a period of 50 years (1966–2016). Results indicate a decrease in high discharge rates during springtime for the Arazkouseh and Galikesh stations, with a steep slope of −0.31 m3/s per year for Arazkouseh and −0.19 and −0.17 for Galikesh. Furthermore, Tamar station experienced an increase in very high discharge during summer, with a slope of 0.12 m3/s per year. However, low discharge rates remained relatively unchanged. Arazkouseh station showed a higher rate of decreasing discharge levels and this trend was most prominent during spring. Additionally, the Bayesian quantile regression model proved to be more accurate and reliable than the frequency-oriented quantile regression model. These findings suggest that quantile regression models are a valuable tool for predicting and managing extreme high and low discharge changes, ultimately reducing the risk of flood and drought damage.
{"title":"Comparison of Bayesian and frequentist quantile regressions in studying the trend of discharge changes in several hydrometric stations of the Gorganroud basin in Iran","authors":"K. Ghorbani, M. Salarijazi, Sedigheh Bararkhanpour, Laleh Rezaei Ghaleh","doi":"10.2166/wcc.2023.305","DOIUrl":"https://doi.org/10.2166/wcc.2023.305","url":null,"abstract":"\u0000 This research utilized Bayesian and quantile regression techniques to analyze trends in discharge levels across various seasons for three stations in the Gorganroud basin of northern Iran. The study spanned a period of 50 years (1966–2016). Results indicate a decrease in high discharge rates during springtime for the Arazkouseh and Galikesh stations, with a steep slope of −0.31 m3/s per year for Arazkouseh and −0.19 and −0.17 for Galikesh. Furthermore, Tamar station experienced an increase in very high discharge during summer, with a slope of 0.12 m3/s per year. However, low discharge rates remained relatively unchanged. Arazkouseh station showed a higher rate of decreasing discharge levels and this trend was most prominent during spring. Additionally, the Bayesian quantile regression model proved to be more accurate and reliable than the frequency-oriented quantile regression model. These findings suggest that quantile regression models are a valuable tool for predicting and managing extreme high and low discharge changes, ultimately reducing the risk of flood and drought damage.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":"1 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67915352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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